Utilization of Ontology to Develop Artificial Intelligence Systems in the Healthcare Industry

Abstract

Objectives: Ontologies play a crucial role in healthcare systems due to the diversity of concepts, roles, users, and diagnosticand therapeutic methods. They facilitate the development of knowledge bases and the sharing and representation of information. With the integration of artificial intelligence (AI) into healthcare, ontologies can serve as complementary tools toenhance the quality of services. Methods: This review study examines existing research on the application of ontologies in AIsystems within the healthcare industry. By analyzing their applications, benefits, challenges, and limitations, the study seeksto provide a deeper understanding of their impact on advancing AI technologies and improving healthcare processes. In addition,the study offers recommendations for strengthening the development and use of ontologies in intelligent healthcaresystems. Results: The findings of this review indicate that ontologies enhance the accuracy of results and support medicaldecision-making by enabling the semantic exchange of diverse and heterogeneous data. They are essential for the developmentof decision support systems and for fostering intelligent interactions between patients and healthcare systems. Furthermore,ontologies contribute to healthcare decision-making by semantically analyzing the connections between diseases, geographicregions, and environmental factors. Conclusions: The use of ontologies in healthcare improves data analysis, patientdiagnosis, treatment, and decision-making. Ontologies enhance data inference and interoperability in AI systems throughdata modeling, concept relationship extraction, knowledge enrichment, and information sharing. Given the vast scope of thehealthcare domain, the diversity of specialties and data, and the absence of a dedicated ontology development methodologyspecific to this field, there is a clear need for a tailored and robust methodology.